Department of Pharmaceutical Engineering, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka 422-8526, Japan.
Int J Pharm. 2011 May 16;409(1-2):81-8. doi: 10.1016/j.ijpharm.2011.02.044. Epub 2011 Mar 1.
Principal component analysis was applied to effectively optimize the operational conditions of a fluidized bed granulator for preparing granules with excellent compaction and tablet physical properties. The crucial variables that affect the properties of the granules, their compactability and the resulting tablet properties were determined through analysis of a series of granulation and tabletting experiments. Granulation was performed while the flow rate and concentration of the binder were changed as independent operational variables, according to a two-factor central composite design. Thirteen physicochemical properties of granules and tablets were examined: powder properties (particle size, size distribution width, Carr's index, Hausner ratio and aspect ratio), compactability properties (pressure transmission ratio, die wall force and ejection force) and tablet properties (tensile strength, friability, disintegration time, weight variation and drug content uniformity). Principal component analysis showed that the pressure transmission ratio, die wall force and Carr's index were the most important variables in granule preparation. Multiple regression analysis also confirmed these results. Furthermore, optimized operational conditions obtained from the multiple regression analysis enabled the production of granules with desirable properties for tabletting. This study presents the first use of principle component analysis for identifying and successfully predicting the most important variables in the process of granulation and tabletting.
主成分分析被应用于有效地优化流化床制粒机的操作条件,以制备具有优异压缩性和片剂物理性能的颗粒。通过一系列制粒和压片实验的分析,确定了影响颗粒性质、可压缩性和最终片剂性质的关键变量。根据两因素中心复合设计,当改变粘合剂的流速和浓度作为独立操作变量时,进行制粒。考察了颗粒和片剂的 13 种物理化学性质:粉末性质(粒径、粒径分布宽度、卡尔指数、哈纳斯比和形状比)、可压缩性性质(压力传递比、模壁力和推出力)和片剂性质(拉伸强度、脆性、崩解时间、重量变化和药物含量均匀度)。主成分分析表明,压力传递比、模壁力和卡尔指数是颗粒制备中最重要的变量。多元回归分析也证实了这些结果。此外,从多元回归分析中获得的优化操作条件使生产出具有可压片性的理想颗粒成为可能。本研究首次使用主成分分析来识别和成功预测制粒和压片过程中最重要的变量。